Battery state-of-health monitoring system and method

• US 8,315,829 B2
• Filed: 06/01/2011
• Issued: 11/20/2012
• Est. Priority Date: 04/22/2008
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations LLC (General Motors Company)
• Inventors: Zhang, Xiaodong
• Primary Examiner(s): Lau, Tung S
• Application Number:
  US13/150,429
• Publication Number:
  US 20110231054A1
• Time in Patent Office: 538 Days
• Field of Search: 702/63
• US Class Current: 702/63
• CPC Class Codes: G01R 31/392 Determining battery ageing or deterioration, e.g. state of health
• CPC Class Codes: H01M 10/4207 for several batteries or cells simultaneously or sequentially
• CPC Class Codes: H01M 10/482 for several batteries or cells simultaneously or sequentially
• CPC Class Codes: Y02E 60/10 Energy storage using batteries

Abstract

A battery state-of-health monitoring and prognosis method includes training off-line parity-relation parameters between extracted battery voltage and current signals during off-line battery discharge events using at least one good off-line battery. Portions of terminal voltage and current signals of an on-board battery corresponding to an on-board engine cranking process are extracted, and battery voltage of the on-board battery are estimated based on the parity-relation parameters and the extracted portions of the on-board battery current signals. A diagnostic residual defining a deviation between the battery voltage estimation of the on-board battery and extracted portions of the on-board battery terminal voltage signals is generated. A measure of battery state-of-health based on the diagnostic residual is then provided.

Claims

1. An on-board battery state-of-health monitoring and prognosis apparatus for a vehicle comprising an engine, comprising:

a signal preprocessing module for extracting portions of on-board battery terminal voltage and current signals after an initial voltage drop during an on-board engine cranking process;

a memory storage device for recalling parity-relation parameters between battery voltage and current signals derived during off-line battery discharge events corresponding to at least one off-line battery capable of delivering a desired power to crank the engine, wherein the parity-relation parameters are trained using a linear regression model;

a voltage estimation module for estimating battery voltage of said an on-board battery based on recalled parity-relation parameters and the extracted portions of the on-board battery current signals extracted during the on-board engine cranking event;

a diagnostic residual generation module for generating a diagnostic residual defining a deviation between the estimated battery voltage of the on-board battery and the extracted portion of the on-board battery terminal voltage signals; and

a residual evaluation module for providing a measure of battery state-of-health based on said diagnostic residual.

2. The apparatus of claim 1, wherein the diagnostic residual generation module comprises a low pass filter.

3. An on-board vehicular battery state-of-health monitoring and prognosis method for a vehicle comprising an engine comprising:

determining off-line parameters of a parity-relation between extracted battery signals using at least one off-line battery capable of delivering a desired power to crank the engine, wherein the parity-relation parameters are trained off-line using a linear regression model;

storing the off-line determined parity-relation parameters in a memory device associated with a voltage estimation module within a battery state-of-health monitoring system on-board the vehicle;

inputting on-board battery terminal voltage and current signals from an on-board battery into a signal preprocessor module within said battery state-of-health monitoring system during an on-board engine cranking event;

extracting after an initial voltage drop during the on-board engine cranking event a portion of the on-board battery terminal voltage and current signals using the signal preprocessor module;

estimating the battery voltage of the on-board battery using the stored off-line determined parity-relation parameters and the extracted portion of the on-board battery current signals;

generating a diagnostic residual with a residual generation module, wherein the diagnostic residual represents a deviation between the estimated battery voltage and the corresponding on-board battery terminal voltage signals; and

evaluating the diagnostic residual in a residual evaluation module to determine a state-of-health metric of the on-board battery.